ebGSEA: an improved Gene Set Enrichment Analysis method for Epigenome-Wide-Association Studies

Bioinformatics
Danyue DongAndrew E Teschendorff

Abstract

The biological interpretation of differentially methylated sites derived from Epigenome-Wide-Association Studies (EWAS) remains a significant challenge. Gene Set Enrichment Analysis (GSEA) is a general tool to aid biological interpretation, yet its correct and unbiased implementation in the EWAS context is difficult due to the differential probe representation of Illumina Infinium DNA methylation beadchips. We present a novel GSEA method, called ebGSEA, which ranks genes, not CpGs, according to the overall level of differential methylation, as assessed using all the probes mapping to the given gene. Applied on simulated and real EWAS data, we show how ebGSEA may exhibit higher sensitivity and specificity than the current state-of-the-art, whilst also avoiding differential probe representation bias. Thus, ebGSEA will be a useful additional tool to aid the interpretation of EWAS data. ebGSEA is available from https://github.com/aet21/ebGSEA, and has been incorporated into the ChAMP Bioconductor package (https://www.bioconductor.org). Supplementary data are available at Bioinformatics online.

References

Dec 25, 2003·Bioinformatics·Jelle J GoemanHans C van Houwelingen
Oct 15, 2010·Nature Biotechnology·Stephan Beck
Jun 5, 2013·Bioinformatics·Paul GeeleherCathal Seoighe
May 31, 2017·Nature Reviews. Genetics·Tuuli Lappalainen, John M Greally
Nov 14, 2017·Nature Reviews. Genetics·Andrew E Teschendorff, Caroline L Relton

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Citations

May 15, 2021·NAR Genomics and Bioinformatics·William R P DenaultAstanand Jugessur
Jun 10, 2021·Genome Biology·Jovana MaksimovicBelinda Phipson
Jul 10, 2021·Epigenomics·Ryu MinegishiSeiichi Mori

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Methods Mentioned

BETA
chips
RNA-Seq

Software Mentioned

Gene Set Enrichment Analysis ( GSEA )
ebGSEA
GSAmeth

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